Neurophysics vs computational neuroscience

Moreover how engineering perspective focused on brain signal analysis and signal processing differ
from those?
Is this approach only for practical purposes like noise reduction from signals and detecting signals which we already understand for example diagnostic applications. And when you have made your filter ready and find something new which isn't yet discovered the one who get to investigate the results is someone else. Or are there science in this approach also in a sense that you can study and explain how the the brain works and make new discoveries with these signals and systems methods.

I'm very interested in the engineering perspective because it gives you a possibility for biomedical engineering which is one of my interest also. I'm just worried about the things i wrote above.

Which one of these approaches do you think is best(promising) for understanding the brain and why?

One difference in tendency between computational neuroscience and bioengineering is the extent to which one uses Maxwell equations. In computational neuroscience, one is often interested in how networks of neurons behave, and the neurons are treated very simply as things that spike once they get input above a certain threshold, analogous to a logic gate. In contrast, in bioengineering one may want to stimulate the neurons to achieve a certain effect, in which case one may use Maxwell's equations to consider how various electrode configurations stimulate the neurons.

As an example, computational neuroscience might use tools like http://www.briansimulator.org/ or http://www.nest-initiative.org/index.php/Software:About_NEST [Broken].